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Geospatial Visualization: Unleashing the Power of Location

Location-enabled data sets are pouring into organizations. Geospatial visualization allows companies to see what’s really going on among the rows and columns.

Geospatial visualization marries the broad insights available through visualization with specific types of analysis that can be performed on location-enabled data. Its power comes from an ability to zero in on key spatial relationships within large structured and unstructured data sets. Visualizing these relationships provides a useful way of organizing large volumes of data. More important, it can reveal fresh insights that would remain hidden without the interpretive combination of analytical integration and the human brain’s amazing ability to discern visual patterns.

Seeing is Believing

In the past, only a handful of industries—oil and gas, governmental agencies, and transportation and logistics—invested in using location as an organizing principle for advanced analysis. New tools and access to more geographically referenced data are now allowing the power of location to be unleashed across many more business areas and to a much broader base of users. New sources feeding the torrent of geospatial information include new structured data from mobile devices (e.g., phones, tablets, other GPS-assisted assets) and new streams of location-aware unstructured data (e.g., from Twitter, Facebook, Foursquare, and Flickr).

Geospatial visualization can enable the human mind to process and detect patterns hidden among huge volumes of information. Spatial analysis provides quantitative evaluation of complex relationships. Time-based animation and other forms of interactive visualization reveal long-term trends and subtle events. Real-time visualization can help drive better decisions on a daily or even hourly basis.

Perhaps most importantly, geospatial visualization’s familiarity and intuitiveness make it one of the most accessible manifestations of analytics. It provides both a compelling and widely usable form of insight derived from information automation and big data.

A case in point: A hardware company used geospatial visualization to understand why customer satisfaction levels had declined. It mapped customer sentiment against service center locations, traffic patterns, and competitor presence. The issue quickly became apparent. To save costs, the company had moved its customer service facilities away from downtown areas, which significantly increased the travel time for customers seeking support at the facilities. These customers were the source of negative feedback. To address their concerns, the company launched an education program on how to use its virtual support channels, initiated on-location services for a handful of large accounts, and simply acknowledged the issue with customers. This allowed the company to win back the good faith of many of its disgruntled customers.

Taking the First Steps

Geospatial visualization should be built on a foundation of solid data management discipline. Once master data management, stewardship, and integration capabilities are bringing good data in, there are a few natural places to start creating compelling visualizations.

Answer the “so what.” The case for geospatial visualization will be more powerful if it is based on detailed business objectives and specific metrics. Flashy new tools or broad-stroke generalities with abstract value will not be persuasive. Issues to consider in building the case include whether geospatial visualization can identify opportunities to save money, improve customer satisfaction, achieve a competitive advantage, or communicate decisions to stakeholders.

Focus on pain points. Each business has pain points that can be used to guide the scope of early geospatial visualization efforts. Logistics and supply chains across distributed organizations are ripe with opportunities. Ask the “where” questions that might lead to new insights. Where are your current customers and where are your next customers likely to be? Where are customers relative to your workforce, warehouses, or service centers? Where are your suppliers? Where are your competitors? If these answers are not easily available, geospatial visualization may help to provide them.

Know your baseline. Many organizations have no idea what data sources and analysis they currently have available, much less the different tools and infrastructure under license among various departments and individuals. To get up to speed, identify the organization’s current state, and compare it with the capabilities needed for modeling, rendering, and interacting with geospatial information. To fill any capability gaps, consider experimenting with subscription-based software-as-a-service models that have a low entry cost.

Find new data, prep old data. Take a close look at new data sources, such as social analytics and demographics, and consider how they could augment your traditional models. This new information can raise new questions and lead to additional insights. Historical data sets will probably need prep work—such as scrubbing and geocoding (determining the location for) addresses—for use in geospatial applications. GPS sensors can also be attached to assets, but don’t go overboard. Limit housekeeping efforts to data that are relevant to the immediate questions and goals at hand.

Democratize with oversight. Visualization can place the power of analytics in more hands across the organization, from the boardroom to customer service centers and the field force. While sharing analytics more broadly helps to convert insights into actions, it also increases the need to manage how information is disseminated and applied. Not all drivers need to be automotive engineers, but someone should be making sure the car is safe to take on the road.

The Bottom Line

Creating visual, interactive, location-based models of complex data can multiply the power of data analytics. Geospatial visualization can provide game-changing support for business decision-making at all levels. Geocoded data and fancy presentation layers are not enough, however, to make good on this potential. Sophisticated analytical models and sound data management disciplines are important stepping stones to simple and effective images supporting sound decisions. Visualization, like many business efforts, should be supported by concrete objectives and well-defined questions. It should also be tested by people with specific experience in both analyzing and communicating location-aware data.

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This publication contains general information only and Deloitte LLP and its subsidiaries ("Deloitte") are not, by means of this publication, rendering business, financial, investment, or other professional advice or services. This publication is not a substitute for such professional advice or services, nor should it be used as a basis for any decision or action that may affect your business. Before making any decision or taking any action that may affect your business, you should consult a qualified professional advisor. Deloitte shall not be responsible for any loss sustained by any person who relies on this publication. Copyright 2012 Deloitte Global Services Limited.

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